The GRADIEND Python Package: An End-to-End System for Gradient-Based Feature Learning
We present gradiend, an open-source Python package that operationalizes the GRADIEND method for learning feature directions from factual-counterfactual MLM and CLM gradients in language models. The package provides a unified workflow for feature-related data creation, training, evaluation, visualization, persistent model rewriting via controlled weight updates, and multi-feature comparison. We demonstrate gradiend through an English pronoun running example, a semantic sentiment use case that evaluates lexical generalization to held-out target words, and a large-scale feature comparison.
| Authors | Jonathan Drechsel, Steffen Herbold |
|---|---|
| Primary category | cs.CL |
| Published | 27 February 2026 |
| Last updated at source | 6 September 2026 |
Popularity, last 3 days
0 now. Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- aieng-lab/en-pronounsDataset · cited by
- aieng-lab/en-pronoun-neutralDataset · cited by
- aieng-lab/en-sentiment-nrc-neutralDataset · cited by
Models and datasets referencing this paper
- aieng-lab/en-pronounsDataset
- aieng-lab/en-pronoun-neutralDataset
- aieng-lab/en-sentiment-nrc-neutralDataset
Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 20 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.